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Revised Cumulative Risk Assessment: Organophosphorus Pesticides Office of Pesticide Programs June 18, 2002 Welcome Lois Rossi, Director Special Review and Reregistration Division Managing Risk From Organophosphorus Pesticides Outline of Presentation Plan for the OPs

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slide1
Revised Cumulative Risk Assessment:

Organophosphorus

Pesticides

Office of Pesticide Programs

June 18, 2002

welcome

Welcome

Lois Rossi, Director

Special Review and Reregistration Division

slide3
Managing Risk

From

Organophosphorus

Pesticides

outline of presentation
Outline of Presentation
  • Plan for the OPs
  • Progress to date
  • Achievements in:
    • Risk reduction
    • Methods development
    • Process improvements
plan for the ops
Plan for the OPs
  • Several OP Reregistration Eligibility Decisions completed before August 1996
  • After August 1996 OPs became a major focus of Reregistration and Tolerance Reassessment
  • In the last six years a tremendous amount of resources dedicated to:
    • Risk assessment and risk management of the individual OP chemicals
    • Developing cumulative risk assessment methods and applying them to the OPs
  • It is appropriate to examine the results and the achievements of the last six years
implementation of the plan
Implementation of the Plan
  • Refine available exposure methods and data
  • Develop a public process to allow greater stakeholder access to information and to facilitate input on:
    • Science policies
    • Exposure data and assumptions
    • Risk assessments
    • Risk management
  • Develop methods for aggregate risk assessment
  • Develop methods for cumulative risk assessment
status of ops
Status of OPs
  • 49 total OPs ever registered
  • 7 cancelled before 1996
    • Chlorfenvinphos, Chlorthiophos, Dialifor, Dioxathion, Monocrotophos, Phosphamidon, Sulprofos
  • 42 started the public participation process
status of ops continued
Status of OPs (continued)
  • 3 early voluntary cancellations
    • Fonofos, Isazophos, Isofenphos
  • 5 recent cancellations
    • Chlorpyrifos methyl, Ethion, Ethyl parathion, Fenamiphos, Sulfotepp
  • 34 OPs remain
status of tolerance reassessment
Status of Tolerance Reassessment

FQPA: Must reassess all tolerances by Aug. 2006

  • 33% by August 3, 1999
    • Completed!
    • Goal 3208, 3290 actually reassessed
  • 66% by August 3, 2002
    • On track for completing goal of 6416
  • 100% by August 3, 2006
    • Final goal: 9721
status of op tolerance reassessment
Status of OP Tolerance Reassessment
  • 1691 at the start of FQPA (1996)
    • 17.4% of all tolerances (9721)
  • 871 reassessed through revocation or other process
  • 98 reassessment underway (revocation)
  • 722 OP tolerances remain to be reassessed
public participation process
Public Participation Process
  • Phase 1 -- Registrant "Error Only" Review (30 days) 
  • Phase 2 -- EPA Considers Registrants Comments (up to 30 days)
  • Phase 3 -- Public Comment on Prel. Risk Asmt. (60 days)  
  • Phase 4 -- EPA Revises Risk Assessments; Technical Briefing (up to 90 days) 
  • Phase 5 -- EPA Solicits Risk Mgmt. Ideas (60 days)
  • Phase 6 -- EPA Develops Risk Mgmt. Strategies (60 days)
public participation process12
Public Participation Process

Individual Reregistration Eligibility Decisions (IREDs)

  • 39 preliminary risk assessments -- public comment
  • 39 revised risk assessments B public comment
  • 32 IREDs/TREDS
  • Communication about each OP: overviews, summaries, fact sheets, comment responses
  • Conference calls and closure calls
  • 18 Technical Briefings
  • Stakeholder meetings B 3 outside DC
public participation process continued
Public Participation Process (continued)

TRAC & CARAT (Advisory Committees)

  • 10 TRAC and 3 CARAT meetings
  • Numerous TRAC and CARAT Workgroup meetings
  • 50+ TRAC/CARAT staff papers
public participation process continued14
Public Participation Process (continued)

Development of Cumulative Assessment

  • 5 Technical Briefings
  • Drinking Water Methodology Workshop
  • Numerous Science Advisory Panel meetings
  • Preliminary assessment B public comment
  • The release of the revised assessment
achievements in risk reduction residential
Achievements in Risk Reduction - Residential -
  • Residential use reduced by >20 million pounds annually
  • Principally as the result of risk mitigation for chlorpyrifos and diazinon
residential continued
Residential (continued)

Universe of chemicals

  • Started with 17 OPs with residential/public area uses
  • 7 OPs excluded from cumulative assessment because residential uses were eliminated/reduced to a negligible level (e.g. limited to bait stations, fire ant mounds)
  • Of the remaining 10, two are limited to public health uses (naled, fenthion)
  • 3 OPs with residential/public area uses still under review (DDVP, malathion, tetrachlorvinphos)
residential continued17
Residential (continued)

Indoor Uses

  • Initially 9 OPs had indoor uses
    • Now only DDVP
  • Initially 6 OPs had pet uses – now only tetrachlorvinphos and DDVP
  • Indoor use of chlorpyrifos, fenitrothion, and trichlorfon limited to pre-packaged child-resistant bait stations (negligible exposure)
residential continued18
Residential (continued)

Protecting Public Health Uses

  • Public Health uses retained where individual assessments indicate no risks of concern
  • Chlorpyrifos fire ant mound treatment
  • Chlorpyrifos mosquito control
  • Fenthion mosquito control
  • Naled mosquito and black fly control
  • Phosmet fire ant mound treatment
residential continued19
Residential (continued)
  • For the cumulative assessment:
    • Used daily residential estimates in probabilistic assessment for the first time
    • developed regional assessments to cover spatial variation throughout the U.S.
  • These advances together will likely have a major impact on future residential risk assessment methodology
achievements in risk reduction food
Achievements in Risk Reduction- Food -
  • Many chemicals faced a much higher standard as the result of the FQPA safety factor requirement
  • This together with generally very low toxicological endpoints for cholinesterase inhibition resulted in extremely low allowable exposures for most chemicals
  • EPA & USDA increased PDP monitoring of OP residues on foods highly consumed by children
  • Agency quickly implemented use of probabilistic dietary exposure estimates on a routine basis
food continued
Food (continued)
  • Most OPs met these very high standards
  • When dietary risks of concern were identified, risks were mitigated:
    • Use removed from OP/crop combination
    • Use pattern changes
      • e.g., rate, frequency, timing
food continued22
Food (continued)
  • Used rigorous methods and high quality data and worked with stakeholders on viable use pattern changes:
    • Addressed dietary risks of concern
    • Limited disruption to agriculture
achievements in risk reduction drinking water
Achievements in Risk Reduction- Drinking Water -
  • OPP now routinely addressing drinking water risks
  • Surface water models enhanced to include a scenario representative of a drinking water reservoir
  • Screening level model developed for groundwater
  • Agency moved on several fronts to obtain improved water monitoring data and is continuing that work
  • Effects of drinking water treatment beginning to be addressed
drinking water continued
Drinking Water (continued)
  • OPs are not a major concern for drinking water (relative to some other classes of chemicals)
  • Time generally allowed for data development when concerns were identified
  • Drinking water risks were mitigated through:
    • Use removed from certain OP/crop combinations
    • Use pattern changes
      • e.g., rate, frequency, timing, use area
drinking water continued25
Drinking Water (continued)
  • For the cumulative assessment:
    • Used daily drinking water estimates in probabilistic assessment for the first time
    • Developed regional assessments to cover spatial variation throughout the U.S.
  • These advances together with improved modeling and monitoring likely to have a major impact on future drinking water risk assessment methodology
achievements in risk reduction worker risk
Achievements in Risk Reduction- Worker Risk -
  • Worker risks are important concern for Ops
  • Very low toxicological endpoints for cholinesterase inhibition often resulted in very low exposures presenting risks of concern
  • Risk/Benefit balancing required an enormous amount of input from stakeholders
worker risk continued
Worker Risk (continued)

Agency worked quickly to complete review of ARTF data

  • Excellent source of extensive, up-to-date data on exposure of re-entry workers
  • Allowed exposures for specific tasks to be calculated separately

PR notice AWorker Risk Mitigation for Organophosphate [email protected]

  • Focused stakeholder attention on worker risks
  • Leveled playing field by stating EPA’s approach
worker risk continued28
Worker Risk (continued)
  • Most chemicals showed some worker risks of concern (handler and/or re-entry)
  • Two chemicals cancelled in large part due to worker risk:
    • Mevinphos (1994)
    • Ethyl parathion (last use date 10/31/03)
worker risk continued29
Worker Risk (continued)

Handler risks addressed in several ways:

  • Closed mixing loading systems applied to many chemicals/scenarios
  • Closed cabs with various levels of respiratory protection applied to many chemicals/scenarios
  • Maximum PPE used in some cases where closed systems not feasible
worker risk continued30
Worker Risk (continued)
  • Most hand held application methods eliminated
  • Certain formulation types (e.g. dusts) eliminated or restricted
  • Reductions in amount handled
    • Reduced rates/frequency of application
    • Some restrictions on amounts used when mixer/loader/applicator is same person
    • Some restrictions on aerial applications
worker risk continued31
Worker Risk (continued)

Re-entry risks addressed in several ways:

  • Tailored to specific problem
  • Significant input from stakeholders
  • Creative solutions in toughest cases (high risks, high benefits), collecting bio-monitoring and will reexamine risks
achievements in risk reduction ecological risk
Achievements in Risk Reduction- Ecological Risk -

Many risk management actions described above also address ecological risks

  • Chlorpyrifos and diazinon mitigation
  • Azinphos methyl: eliminated use on sugarcane and cotton in large part due to aquatic concerns
  • Decreased rates/application frequency; limited area covered (e.g. on golf courses, change from broadcast to spot treatments)
ecological risks continued
Ecological Risks (continued)

Other risk mitigation methods utilized:

  • Watering in/incorporation of granules
  • Altered timing of applications to reduce exposure to wildlife at most vulnerable times (e.g. nesting)
  • Developed new disposal methods for cattle dip vats (coumaphos)
  • Buffer zones (for spray drift)
  • Addressed special risk concerns (e.g. honey bees)
  • Addressed special habitat concerns (fenthion)
  • Improved labeling (e.g. emphasize best management practices)
summary
Summary
  • Major accomplishment in which many people played an important role
  • Better results when people work together
  • Establishment of an effective public participation process ensures the continuation of a productive working relationship
science assessment

Science Assessment

Staff from the Health Effects Division and Environmental Fate and Effects Division

slide36
General Overview and Introduction

Randolph Perfetti, Ph.D

Associate Director,

Health Effects

roadmap
Roadmap
  • Background
  • Activities Since the Preliminary Assessment
  • Major Revisions in This Assessment
  • Highlights of Sensitivity Analyses
background
Background
  • FQPA 1996 requirements
  • Methods development
  • SAP reviews and public comments, technical briefings
  • Development of Preliminary Assessment
  • Revised Assessment
what is this cumulative assessment
What is this Cumulative Assessment
  • Multiple chemicals with common mechanism of toxicity
  • Multiple routes of exposure
  • Multiple pathways of exposure
roadmap40
Roadmap
  • Background
  • Activities Since the Preliminary Assessment
  • Major Revisions in This Assessment
  • Highlights of Sensitivity Analyses
activities since preliminary assessment
Activities Since Preliminary Assessment
  • Addressed the FQPA Safety Factor
  • Incorporation of new food processing factors
  • Sensitivity analyses
  • SAP review
  • Public comments and technical briefing
roadmap42
Roadmap
  • Background
  • Activities Since the Preliminary Assessment
  • Major Revisions in This Assessment
  • Highlights of Sensitivity Analyses
major differences
Major Differences
  • Hazard/ Dose Response
    • Relative Potency Factors
    • FQPA Factors
  • Food Exposure
    • New processing factors
    • Over- tolerance residues
    • Time frames
    • Populations Considered
major differences44
Major Differences
  • Water
    • Number of regions
    • Populations considered in Region A
  • Residential
    • Number of regions
    • Distributions used
    • Populations considered in Region A
    • Pet uses
major differences45
Major Differences
  • Regional
    • Preliminary OP CRA – 13 regions
    • Revised OP CRA – 7 regions
    • 7 regions effectively describes geographical/climatological differences
risk characterization
Risk Characterization
  • Summarizes and integrates all of the information from the various components of the assessment.
  • Looks at:
    • Strengths and weaknesses of the data used including any potential biases in input parameters and the direction of that bias,
    • Reliability and availability of the data, as well as the characteristics of the exposure models, and attempts to bound that uncertainty.
  • The revised assessment discusses in great detail what data have been used; how the data have been used; and the strengths and weaknesses of the resulting analysis.
roadmap50
Roadmap
  • Background
  • Activities Since the Preliminary Assessment
  • Major Revisions in This Assessment
  • Highlights of Sensitivity Analyses
sensitivity analysis definition
Sensitivity Analysis: Definition

Sensitivity analysis is used to increase the confidence in the model and its predictions by providing an understanding of how the model response variables respond to changes in the inputs.

highlights of sensitivity analyses
Highlights of Sensitivity Analyses
  • Food
    • Analysis of consumption and residue extremes
    • Imported crops
    • ½ LOD
    • Translation of residue data
    • Market Basket Survey
highlights of sensitivity analyses53
Highlights of Sensitivity Analyses
  • Drinking Water
    • Additional comparisons of monitoring data vs. estimated concentration
    • Water treatment effects/ conversion to active metabolites
    • Typical and maximum application rates
    • Impact of estimated spray drift loading
highlights of sensitivity analyses54
Highlights of Sensitivity Analyses
  • Residential
    • Log normal vs. uniform distributions
    • QA/QC of Regional Analyses
the science team
David Miller

Public Health Service

Anna Lowit, Ph.D. Toxicologist

Vicki Dellarco, Ph.D. Senior Science Advisor

Beth Doyle, Ph.D.

Branch Chief

Nelson Thurman

Senior Environmental Scientist

David Hrdy,

Biologist

The Science Team
slide56
The FQPA Safety Factor Analysis

Vicki Dellarco, Ph.D.

Senior Science Advisor

Health Effects Division

slide57
Determination of the Appropriate FQPA Safety Factor(s) in the Organophosphorus Pesticide Cumulative Risk Assessment

Evaluation of Sensitivity and Susceptibility to the Common Mechanism of Toxicity, Acetylcholinesterase Inhibition

topics
Topics
  • Background
    • FQPA 10X Safety Factor Provision
    • Science Policy Papers
    • Public Comments on Guidance
  • Analysis of Sensitivity & Susceptibility
    • Key Questions
    • Available Data
    • Conclusions
  • June SAP Meeting
    • Questions
fqpa 10x safety factor provision
“in the case of threshold effects…an additional tenfold margin of safety …shall be applied for infants and children …”

“the Administrator may use a different margin of safety for the pesticide chemical residue only if, on the basis of reliable data, such margin will be safe for infants and children.”

FQPA 10X Safety Factor Provision
fqpa provision
FQPA Provision
  • FQPA establishes a presumption in favor of applying an additional 10X safety factor
    • Can depart from default FQPA 10X approach when reliable evidence shows that a different safety factor is protective of infants & children
fqpa provision61
“take into account…potential pre- and post-natal toxicity and completeness of the data with respect to exposure and toxicity to infants and children”FQPA Provision
science policy papers
Science Policy Papers

http://www.epa.gov/oppfead1/trac/science/determ.pdf

http://www.epa.gov/oppfead1/trac/science/consid_draft.pdf

fqpa safety factor guidance
FQPA Safety Factor Guidance
  • Completeness of toxicity data
  • Degree of concern for pre-& postnatal toxicity
  • Completeness of exposure data

Guidance Structured Around 3 Areas of Analysis

fqpa safety factor determinations cumulative risk assessment
FQPA Safety Factor Determinations:Cumulative Risk Assessment
  • Analysis focuses on common mechanism of toxicity & associated effects in the young

Acetylcholinesterase

fqpa safety factor determination cumulative risk assessment
FQPA Safety Factor Determination: Cumulative Risk Assessment
  • If uncertainty pertains to specific chemical members
    • Use uncertainty factor to adjust relative potency factor (RPF) on a chemical specific basis
  • If uncertainty generally shared by the chemical group
    • Apply uncertainty factor as group factor after determining Margin of Exposures (MOE)
public comments on guidance
Public Comments on Guidance
  • Public Comment Draft, February 28, 2002
    • “Consideration of the FQPA Safety Factor and Other Uncertainty Factors in Cumulative Risk Assessment of Chemicals Sharing a Common Mechanism of Toxicity;”
public comments uncertainty safety factor op cra
Public Comments Uncertainty/Safety Factor: OP CRA
  • 10X intraspecies factor is adequate to protect children from effects of OPs
    • 1X interspecies factor should be used because rats & humans respond similarly to effects of OPs
  • Age-related sensitivity found in rats not relevant to children
    • Direct dosing via gavage
    • Difference between human & rat development
    • Effects found at high toxic doses

Comments Supporting Removal of FQPA Factor

public comments uncertainty safety factor op cra68
Public Comments Uncertainty/Safety Factor: OP CRA
  • Children are not at a greater risk
    • Will have adult levels of detoxification enzymes by time they are consuming fruits & vegetables
  • Should not impose uncertainty factors for the absence of data from newly required studies (DNT)

Comments Supporting Removal of FQPA Factor

public comments uncertainty safety factors op cra
Public Comments Uncertainty/Safety Factors: OP CRA
  • RPFs based on adult data require an FQPA safety factor of at least 10
    • DNT studies not available for many OPs
    • Some OPs have demonstrated developmental effects
    • Exposures at critical windows of neurodevelopment can lead to permanent and adverse effects
  • More distinct age groups need to be considered

Comments Supporting Retention of FQPA Factor

public comments uncertainty safety factors op cra70
Public Comments Uncertainty/Safety Factors: OP CRA
  • Need to account for effects that could occur below those doses used to calculate RPFs & PoDs
  • Toxic degradate & metabolites need to be considered
  • All sources of exposure need to be considered (violative residues, spray drift, nonagricultural contribution to water, food purchased at farmers markets, etc)

Comments Supporting Retention of FQPA Factor

ii analysis of susceptibility sensitivity

II. Analysis of Susceptibility & Sensitivity

Prepared jointly by Scientists from

Office of Pesticide Programs &

Office of Research & Development

fqpa conclusions
FQPA Conclusions
  • Completeness of Toxicity Data
    • Apply database uncertainty factor to most OPs to account for potential age-dependent sensitivity in children based on biological evidence
  • Concern for Pre-& Postnatal Toxicity
    • No additional concern if potential age-dependent sensitivity is accounted for
  • Completeness of Exposure Data
    • No additional concern, based on comprehensive & data-specific exposure assessment
what are the potential toxicities in the young
What are the Potential Toxicities in the Young?
  • Cholinergic toxicity
  • Neurodevelopmental Effects

Inhibition of AChE can potentially lead to adverse effects in the young

Acetylcholinesterase

what is the most sensitive endpoint
What is the Most Sensitive Endpoint?

Important to address age-related sensitivity of ChE inhibition to account for potential pre- & postnatal toxicity

  • When neurodevelopmental effects are found, they do not occur at doses below those that cause ChE inhibition in young and/or dam

Acetylcholinesterase

focus age dependent sensitivity to cholinesterase inhibition
Focus: Age Dependent Sensitivity to Cholinesterase Inhibition
  • Will the young show cholinesterase inhibition at lower doses than adults or at the same dose will be inhibited more?

Acetylcholinesterase

slide76
Comparative Cholinesterase Data Available for OP Pesticides in Postnatal versus Adult Rats

Acephate Azinphos-methyl Bensulide

ChlorethoxyfosChlorpyrifosChlorpyrifos-methyl

Diazinon Dichlorvos Dicrotophos

DimethoateDisulfoton Ethoprop

Fenamiphos FenthionMalathion

Methamidophos Metidathion Methyl Parathion

Mevinphos Naled Oxydemeton-methyl

Phorate Phosolone Phosmet

Phostebupirim Pirimiphos-methyl Profenofos

Terbufos Tetrachlorvinphos Tribuphos

Trichlorphon

age dependent sensitivity in rats
Age Dependent Sensitivity in Rats
  • Postnatal (direct dosing)
    • Some OPs caused age dependent sensitivity, but not all
  • Fetuses
    • Unknown, but less inhibition in fetus is typically seen compared to dam
why is age dependent sensitivity found in rat pups
Why is Age Dependent Sensitivity Found In Rat Pups?
  • Biological Factor
    • Immature rats appear to be more sensitive to some OP pesticides because they lack detoxification capability via A-esterases and/or carboxylesterases
generic op metabolic pathway
Generic OP Metabolic Pathway

Oxon

OP Pesticide

Liver Activation

Detoxification

Bind to

CaEs

Detoxification

Hydroylzed by

A-Esterases

Inhibit

AChE

summary of current knowledge
Summary of Current Knowledge

Derived from rat studies

fqpa safety factor provision
FQPA Safety Factor Provision
  • Issues
    • Potential for age-dependent sensitivity AND
    • Incomplete data for cholinesterase activity in the young for many OP pesticides
  • Approach
    • Address FQPA provision “completeness of the toxicity data” with database uncertainty factor
    • Adjust RPF values, except for those OPs that do not show age-dependent sensitivity
developmental stages
Developmental Stages
  • Acute Dose Rat Study
    • Treatment at Postnatal Day (PND) 7 or 11 (similar to a human infant <6 months)
  • Repeated Dosing Rat Study
    • Treatment from PND 11 to 21 & measured at PND 21 (similar to a 1-2 year old)
developmental stages85
Developmental Stages
  • Highly Exposed Children’s Age Group
    • 1 & 2 yr, not infant < 1yr
  • Maturation Profile of A-Esterase
    • Rats
      • Increases from birth to reach adult levels around postnatal day 21
    • Humans
      • After birth steady increase during the first 6 months to about 12 to 15 months of age
developmental stages86
Developmental Stages
  • Relative sensitivities found in repeated dosing studies better approximate maturation profile of highly exposed children’s age group (1-2 year olds)
why use repeated dose rat study versus acute study
Why Use Repeated Dose Rat Study Versus Acute Study?
  • Exposure to an OP occurs every day via food
  • Following exposure to an OP, re-synthesis of ChE to pre-exposure levels does not occur for days (or weeks)
  • Biomonitoring studies suggest an existing body burden to OP pesticides
size of fqpa safety factor
Size of FQPA Safety Factor
  • Consideration for selecting 3X FQPA Safety Factor
    • ChE Data on 6 OP Pesticides
      • At relevant ages, sensitivities ranged from 1X (no difference) up to about 3X difference
      • Greater sensitivities (≤10X) occur only at “newborn”, low exposure stage
size of fqpa safety factor continued
Size of FQPA Safety Factor (continued)
  • Consideration for selecting 3X FQPA Safety Factor
    • Potential for other OPs to show age dependent sensitivity, but difference is not expected to be great between human 1 & 2 year olds & adult
size of fqpa safety factor continued90
Size of FQPA Safety Factor (continued)
  • Consideration for selecting 3X FQPA Safety Factor
    • Some human infants will rapidly reach adult levels of blood A-esterases at 6 months, and some uncertainty around 1-2 years
slide91
Comparative Cholinesterase Data Available for OP Pesticides in Postnatal versus Adult Rats

3X-Acephate 3X-Azinphos-methyl 3X-Bensulide

3X-Chlorethoxyfos1X-Chlorpyrifos3X-Chlorpyf-M

3X-Diazinon 3X-Dichlorvos 3X-Dicrotopho

1X-Dimethoate3X-Disulfoton 3X-Ethoprop

3X-Fenamiphos 3X-Fenthion3X-Malathion

1X-Methamidophos 3X-Metidathion3X-MethylPara

3X-Mevinphos 3X-Naled 3X-ODM

3X-Phorate 3X-Phosolone 3X-Phosmet

3X-Phostebupirim 3X-Pirimiphos-methy 3X-Profenofos

3X-Terbufos 3X-Tetrachlorvinphos 3X-Tribuphos

3X-Trichlorphon1X-Omethoate (by extension)

slide92
Relative Potency Factors Based on Adult Rat Brain (Female) Cholinesterase Data

RPF = BMD10 OPx

BMD10 Index

(methadmidophos)

fqpa conclusions93
FQPA Conclusions
  • Completeness of Toxicity Data
    • Apply database uncertainty factor to most OPs to account for potential age-dependent sensitivity in children based on biological evidence
  • Concern for Pre-& Postnatal Toxicity
    • No additional concern if potential age-dependent sensitivity is accounted for
  • Completeness of Exposure Data
    • No additional concern, based on comprehensive & data-specific exposure assessment
completeness of exposure data
Completeness of Exposure Data

Food

Exposure

Drinking Water

Exposure

Residential

Exposure

completeness of the exposure data
Completeness of the Exposure Data
  • Several Different Age Groups
    • All pathways
      • 1-2 yr & 3-5 yr
    • Food
      • Infants < 1 yr; 1-2 yr; 3–5 yr; 6-12 yr, 13-19 yr
    • Florida Regional Residential & Drinking Water
      • Infants < 1 yr; 1-2 yr; 3–5 yr; 6-12 yr, 13-19 yr
slide96
Completeness of the Exposure Data: Food
  • Consumption Data (CSFII &1998 Supplemental Children’s Survey)
  • Residue Monitoring Data (USDA PDP, FDA, Market Basket Surveys)
  • Residues in Commercial Baby Food
  • Baby Formula
  • Breast Milk (qualitatively)
  • OP metabolites
completeness of the exposure data drinking water
Completeness of the Exposure Data: Drinking Water
  • PRZM-EXAMS Index Reservoir Model
  • Pesticide Use Data (USDA NASS, CDPR, USDA)
  • Regional approach (12 regions)
    • Captures more vulnerable surface watersheds
  • OP metabolites (oxon forms) qualitatively considered
completeness of the exposure data residential
Completeness of the Exposure Data: Residential
  • Remaining residential uses
    • Applications to home lawn & garden, pets, golf courses, of public health pests
  • All routes
  • Chemical-specific residue data
  • Activity patterns of children
  • Probabilistic techniques
fqpa conclusions99
FQPA Conclusions
  • Completeness of Toxicity Data
    • Apply database uncertainty factor to most OPs to account for potential age-dependent sensitivity in children based on biological evidence
  • Concern for Pre-& Postnatal Toxicity
    • No additional concern if potential age-dependent sensitivity is accounted for
  • Completeness of Exposure Data
    • No additional concern, based on comprehensive & data-specific exposure assessment
sensitivity analysis of 3x uncertainty factor
Sensitivity Analysis of 3X Uncertainty Factor

Impact on MOEs

Food Pathway ( 1-2 yr olds)

99.9 99 95

1.2X 1.3X 1.5X

[1XRPFs versus 3XRPFs for all OPs EXCEPT those that do not show age dependent sensitivity]

june scientific advisory panel review
June Scientific Advisory Panel Review
  • Role of AChE in Development
  • Age-Dependent Sensitivity in Animal Studies
  • Relevance of Animal Findings to Children
slide102
Cumulative Hazard and Dose-Response Assessment:

Organophosphorus Pesticides

Anna Lowit, Ph.D.

Toxicologist,

Health Effects Division

relative potency factor method
Relative Potency Factor Method
  • Relative toxic potency of each chemical was calculated in comparison to “index chemical”
  • Exposure equivalents of index chemical are combined in the cumulative risk assessment
    • Methamidophos is the Index Chemical
preliminary cumulative risk assessment dec 01
Preliminary Cumulative Risk Assessment (Dec ’01)
  • Oral Route
    • RPFs calculated for 29 OPs
    • Exponential model used to estimate benchmark doses (BMD10s)
      • Basic Model---Low dose region of dose-response curve is linear.
      • Expanded Model—Low dose region of dose-response curve is flat
preliminary cumulative risk assessment dec 01105
Preliminary Cumulative Risk Assessment (Dec ’01)
  • Dermal and Inhalation Routes: CELs
    • Comparative effect levels
      • Applicable only to the common mechanism effect
    • Dose-response modeling was not performed
updates and revisions to rpfs
Updates and Revisions to RPFs
  • Oral Route
    • RPFs for 4 Additional OPs:
      • chlorethoxyphos, omethoate, profenofos, and phostebupirim
    • New toxicity studies for:
      • disulfoton, fenamiphos, phosalone, tetrachlorvinphos, and tribufos
    • Updated data set of ChE data can be found at

http://www.epa.gov/pesticides/cumulative/rra-op/

updates and revisions to rpfs107
Updates and Revisions to RPFs
  • Oral Route
    • Benchmark dose calculation errors corrected
    • Results:
      • Basic Model---16 OPs
      • Expanded Model—17 OPs
analysis of power to detect a bmd 10
Analysis of Power to Detect a BMD10
  • EPA Draft Benchmark Dose Guidance (2000) indicates that the BMD should lie at the low end of the range of the responses but within assay detectability.
  • The BMD10 was selected as the effect level for the RPFs and PODs in the CRA
  • Analyzed the power to detect various degrees of rat brain ChE inhibition
analysis of power to detect a bmd 10109
Analysis of Power to Detect a BMD10
  • Analyzed the power to detect various degrees of rat brain ChE inhibition
    • Power of a Study:
      • Ability of a study to detect a given amount of change
      • In general, depends on the sample size and the variability of the data
    • 1%, 5%, 7.5%, 10%, 15%, and 20%
analysis of power to detect a bmd 10110
Analysis of Power to Detect a BMD10
  • Analyzed the power to detect various degrees of rat brain ChE inhibition
      • Power > 0.80 is the conventional goal for determining adequate power for detecting an effect
      • At 1%, 5%, 7.5%, median power is too low

(i.e, can not consistently detect)

      • At 10%, median power is 0.89 (i.e, can consistently detect)
      • 10% brain ChE inhibition is indeed in the low end of detectability
sensitivity analysis individual data vs summary data
Sensitivity Analysis: Individual Data vs. Summary Data
  • RPFs and PODs in CRA are based on summary data extracted from toxicology studies
    • Mean, standard deviation, sample size
  • Issue discussed by SAP:
    • What is the impact of summary data on the BMD10 calculations?
    • Would the use of individual animal data impact the BMD10 calculations?
sensitivity analysis individual data vs summary data112
Sensitivity Analysis: Individual Data vs. Summary Data
  • Individual animal data for 15 toxicology studies in the CRA were available.
  • Analysis showed that the use of summary data did not impact the BMD10 in CRA
    • Methamidophos:
      • BMD10 s of 0.080 mg/kg/day vs. 0.079 mg/kg/day
table of pods
Table of PODs

Points of Departure for Methamidophos, the Index Chemical

Oral

0.08 mg/kg/day

Dermal

2.12 mg/kg/day

Inhalation

0.39 mg/kg/day

slide116
Food Exposure Assessment Process

William O. Smith, Ph.D

Health Effects Division

roadmap117
Roadmap
  • Review of Food Methods
  • Revisions Since Preliminary Assessment
  • Brief Account of Food Results
  • Some Analysis of Results
methods used in food assessment
Methods used in Food Assessment

DEEM-FCID™ to estimate cumulative dietary exposure and for analysis of contribution of chemicals and foods to exposure.

Calendex ™ software to estimate aggregate exposures from food, water, and residential exposures over different time intervals.

methods used in food assessment119
Methods used in Food Assessment

Discussions in this sections are limited to one day assessments of food exposure using DEEM-FCID™ in order to best illustrate refinements to the analysis.

Later in this briefing the results from Calendex ™ will be discussed for multiple time frames.

methods used in food assessment120
Methods used in Food Assessment
  • Dietary Exposure Evaluation Model – DEEM-FCID™
  • Probabilistic (Monte-Carlo) procedure
  • Input:
    • Distributions for consumption & residues
  • Output:
    • Distribution of one-day dietary exposures
methods use in food assessment
Methods use in Food Assessment
  • Input data for DEEM-FCID™ and Calendex ™
    • Food consumption
      • CSFII 1994-96/1998
    • Residues on foods
      • OP CRA Food Residue Database
csfii 1994 96 1998
CSFII 1994-96/1998

Food Model-Consumption Data

  • Intakes of 20,607 individual participants interviewed over two discontinuous days
  • 1998 Supplemental Children’s Survey
  • Incorporated in DEEM-FCID™ software
food model residue data
Food Model-Residue Data

OP CRA Food Residue Database

  • Residue Data
  • Processing Factors
  • Relative Potency Factors
  • Data Translation schemes
  • Algorithms for estimating cumulative residue distributions
roadmap124
Roadmap
  • Review of Food Methods
  • Revisions Since Preliminary Assessment
  • Brief Account of Food Results
  • Some Analysis of Results
revisions in food assessment
Revisions in Food Assessment
  • Beans, peas, peaches, pears, spinach, and parsley: All boiled food forms
  • Tomato processed food forms

Changes in Source of Residue Data

PDP-canned

PDP-fresh

revisions in food assessment126
Revisions in Food Assessment
  • Apple sauce residue data changed from PDP fresh apples to apple sauce market basket data
  • Lettuce: Removed 1994 residue data
revisions in food assessment127
Revisions in Food Assessment

Processing Factor changes made for:

17 Chemicals on ~550 Food Forms

revisions in food assessment128
Revisions in Food Assessment
  • Relative potency factors revised
  • FQPA factors incorporated via relative potency factors.
    • 1x for chlorpyrifos, dimethoate/omethoate, and methamidophos
    • 3x for all other chemicals in assessment
revisions in food assessment129
Revisions in Food Assessment
  • Chlorpyifos methyl and femamiphos removed from assessment
  • Selected chemical/crop combinations were added or removed to match currently supported uses and tolerances
  • Tolerance exceeding residues were added back to the assessment base on SAP recommendation
revisions in food assessment130
Revisions in Food Assessment
  • Section 3 Registration
  • Section 24(c) SLN Registration
  • Tolerance for import commodities only

Conditions for Inclusion

in this Assessment

revisions in food assessment131
Revisions in Food Assessment
  • Exposure was assessed over different time frames
    • 1-day
    • 7-day, 14-day and 21-day averages
  • Output distributions are being reported for more age groups (7 groups)
revisions in food assessment132
Revisions in Food Assessment

The data and documentation of changes will be available on internet

http://www.epa.gov/pesticides/cumulative/rra-op/

  • Appendices to the revised risk assessment
  • OP CRA Food Residue Database
roadmap133
Roadmap
  • Review of Food Methods
  • Revisions Since Preliminary Assessment
  • Brief Account of Food Results
  • Some Analysis of Results
roadmap138
Roadmap
  • Review of Food Methods
  • Revisions Since Preliminary Assessment
  • Brief Account of Food Results
  • Some Analysis of Results
analysis of upper portion of exposure distribution for children 1 2
Analysis of Upper Portion of Exposure Distribution for Children 1-2

DEEM CEC

Top daily exposure records in distribution

  • Provides demographics on individuals
  • Identifies the amount of foods consumed
  • Identifies the residue level in each food
analysis of upper portion of exposure distribution for children 1 2140
Analysis of Upper Portion of Exposure Distribution for Children 1-2

OP CRA Food Residue Database

  • Tracks all original data contained in each residue distribution
  • Provides links between chemicals and food forms
analysis of upper portion of exposure distribution for children 1 2141
Analysis of Upper Portion of Exposure Distribution for Children 1-2

Food consumption Records for top 0.2

percentile of the exposure distribution

Chemical and sample specific data

contributing to residues in top

consumption records

slide142
Most Significant Chemicals in the Top 0.2 Percentile

Of Exposure for Children 1-2

Chemical

Percentage of

Total

Exposure

Dimethoate/Omethoate

48 %

Azinphos methyl

27%

Acephate/methamidophos

11%

Methamidophos

5%

Phosmet

2.4%

Phorate

2.2%

slide143
Most Significant Foods In Top 0.2 percentile

of Exposure for Children 1-2

Food

Food Form

Fraction of Total Exposure

Grape

Uncooked; Fresh or N/S; Cook Meth N/S

0.33

Pear

Uncooked; Fresh or N/S; Cook Meth N/S

0.16

Apple, fruit with peel

Uncooked; Fresh or N/S; Cook Meth N/S

0.13

Apple, juice

Uncooked; Fresh or N/S; Cook Meth N/S

0.10

Tomato

Uncooked; Fresh or N/S; Cook Meth N/S

0.05

Grape, raisin

Uncooked; Dried; Cook Meth N/S

0.04

Bean, snap, succulent

Cooked; Frozen; Boiled

0.03

Pepper, bell

Uncooked; Fresh or N/S; Cook Meth N/S

0.03

Bean, snap, succulent

Cooked; Canned; Boiled

0.02

All Other Commodities

 0.01

slide144
Most Significant Consumers in the Top 0.2 Percentile of Exposure for Children 1-2
  • OPP has examined various aspects of top consumers
  • Distribution of consumption for foods that contribute to upper portion of exposure distribution
    • Overall “pattern” or distribution of consumption values
    • Magnitude of high-end consumption values
    • Predominance of high-end consumption values
slide145
lndividuals With Highest Reported Consumption Values of the Most Significant Foods (in the top 0.2 Percentile of Exposure)
role of imported foods in assessment
Role of Imported Foods in Assessment
  • Comparing Exposure with/without import samples contributing to residues
  • Result: With import samples, 12-18% increase in exposure at upper percentiles.
slide147
Calendar-Based Exposure Assessment

Calendex ™ was used to estimate aggregate exposures from food, water, and residential exposures over different time intervals.

These assessments and related issues will be discussed later in this briefing

slide148
Drinking Water Exposure Assessment for

the Revised OP Cumulative Risk Assessment

Nelson Thurman

Senior Environmental Scientist

Environmental Fate & Effects Division

road map
Road map

http://www.epa.gov/pesticides/cumulative/rra-op/

  • What we did (I.E. Water OP Cumulative Risk)
    • Brief recap with focus on what’s new
  • What we found (II.A-G. Regional Assessments)
    • Some analyses of results
    • Comparison with monitoring (also Appendices III.E.1, III.E.3)
  • What it means (I.H. Risk Characterization)
    • Follow-up analyses (also Appendix III.E.11)
cumulative drinking water assessment team
EFED

Kevin Costello

Ian Kennedy

Stephanie Irene

Nelson Thurman

Many more…

OP chemical teams

Monitoring reviews

Model development

Treatment effects

Follow-up analyses

HED

Steve Nako

David Miller

David Hrdy

Bernard Schneider

Yuen-Shaung Ng

BEAD

Leo Lasota

Art Grube

SRRD

Laura Parsons

Cumulative drinking water assessment team
what we needed for the cumulative drinking water exposure
What we needed for the cumulative drinking water exposure
  • Distribution of daily concentrations for probabilistic exposure assessment
  • Variations in time (daily, seasonally, yearly)
  • Variations in place for drinking water
  • Co-occurrence of multiple chemicals as they occur together in place and time
what we knew from monitoring
What we knew from monitoring
  • OPs are found in drinking water sources, often not frequently or at high levels
    • Chlorpyrifos, diazinon, malathion most frequent
    • Most detections in single parts per billion or lower
    • Multiple OPs detected together
  • Surface water sources generally more vulnerable
  • Transformations by drinking water treatment
    • Oxons, sulfoxides and sulfones
key components of water exposure
Key components of water exposure
  • Daily distribution over multiple years
  • Started at regional level (7 regions)
  • Watershed-based modeling (PRZM-EXAMS)
    • Multiple fields with multiple chemical uses
    • Adjustments for area treated
  • “Typical” usage patterns
  • Estimates compared with monitoring
daily distributions reflected weather variations over multiple years for multiple chemicals
Daily distributions reflected weather variations over multiple years for multiple chemicals

Region G

regional approach focused on vulnerable areas
Regional approach focused on vulnerable areas
  • Where are OPs used? How much? What crops? What kinds of DW intakes? How vulnerable?

Region B

Region D

Region E

Region C

Region A

Region G

Region F

each regional dw location reflects
Each regional DW location reflects …
  • Geographic area with high potential for combined (cumulative) OP exposure
    • Influenced by relative potency factors
  • Location-specific conditions
    • environmental data (soil/site, weather, crops)
    • Major crop-OP combinations within that area
  • More vulnerable drinking water sources within the region
each regional op cumulative distribution reflects
Each regional OP cumulative distribution reflects…
  • Amount of each OP used in the watershed
    • Typical rates x acres treated x no. applications
    • Based on current use, including risk management actions
  • Timing of each OP use
    • Application windows
  • Relative potency and safety factors
preliminary feedback from sap 2 02
Preliminary feedback from SAP (2/02)
  • Scientifically sound; appropriate use of models
  • Approach seems health-protective
    • Further monitoring comparisons, sensitivity analyses needed
  • Issues raised in SAP review
    • Application rates
    • Spray drift contributions
    • Treatment by-products (oxons)
regional cumulative op distributions
Regional cumulative OP distributions

Reg A

Regional distributions reflected

short-pulse trends, with peak

concentrations generally no greater

than single ppb and declining

rapidly to near-zero concentrations

Reg G

Reg D

Reg E

Reg F

Reg C

Reg B

cumulative drivers in each region
Cumulative drivers in each region
  • Typically 1 or 2 OPs were major drivers
  • Generally higher RPF chemicals
    • Terbufos (0.85), phorate (0.39), disulfoton (1.26), dicrotophos (1.91)
  • Tended to be OPs that formed sulfoxides, sulfones rather than oxons
comparisons with monitoring data
Comparisons with monitoring data
  • NAWQA: Appendix III.E-1
    • Different water bodies, not drinking water
    • Different time periods, sample frequencies
    • In each region, estimates comparable to monitoring (within a factor of 10)
      • Some higher (>10X): reflects mobile, persistent sulfoxide/ sulfone degradates (ex., phorate, terbufos)
      • Some lower (<10X): reflects cancelled/phased-out uses (ex., diazinon, azinphos methyl)
comparisons with nawqa monitoring
Comparisons with NAWQA monitoring

Chlorpyrifos in Region D

comparisons with monitoring data165
Comparisons with monitoring data
  • USGS-EPA Reservoir Monitoring: Appendix III.E-3
    • Detections, frequencies generally less than estimated concentrations, but not by orders of magnitude
    • Many reservoirs outside high use areas
    • Small time frame; extreme weather conditions

NY Reservoir; Source: USGS

impact of treatment by products
Impact of treatment by-products
  • Assessment already accounts for sulfoxide, sulfone transformation products
  • Conversion of OP parents to oxons unlikely to add significantly to the cumulative OP load
    • OP pesticides which form oxons do not contribute significantly to the cumulative “pulse”
    • Oxon-forming OP pesticides frequently detected in water (chlorpyrifos, diazinon, malathion) have low RPFs in comparison to other OP pesticides
treatment by products oxons region g
Treatment by-products: Oxons (Region G)

Assumes oxons 10X more toxic

chlorpyrifos, dimethoate, malathion,

methyl parathion, phostebupirim

what do the analyses tell us
What do the analyses tell us?
  • Estimated distributions in each region
    • Generally comparable to monitoring
    • Represent high-exposure water sources
  • Typical application rates
    • Represent actual use
    • Using maximum rates, estimated concentrations no more than 2-4X greater than concentrations estimated using typical rates
what do the analyses tell us171
What do the analyses tell us?
  • Spray drift is not a factor in most regions
    • Accounts for no more than 1-2% of total OP load in 6 regions; even less of pulse loads
    • May account for majority of OP load in arid west, where runoff events are rare (to be expected)
  • Conversion to oxons is not expected to be a factor
    • Regional drivers are not oxon-forming OPs
    • Little or no effect (<2X) at 75th percentile or higher
slide172
Residential Exposure Assessment Process

Jeff Evans

Senior Scientist

Health Effects Division

residential op assessment use changes
Residential OP Assessment: Use Changes

Indoor Use: DDVP (pest strip use in closets and cupboards)

Pet Use: Tetrachlorvinphos (spray/dip/powder)

collars: only qualitatively assessed

Home Lawns: Bensulide, Trichlorfon

Golf Course: Acephate, Bensulide,Fenamiphos, Trichlorfon

residential op assessment use changes174
Residential OP Assessment: Use Changes

Home Garden: Acephate and Disulfoton ornamental), Malathion (ornamental and edible food)

Malathion dust formulation removed

Public Health: Fenthion, Malathion, Naled

age groups
Age Groups

Assessment performed for the following age groups:

  • Children 1-2 years old
  • Children 3-5 years old
  • Adults 20+

All ages assessed for Region A (as an appendix)

regional changes
Regional Changes
  • PCRA assessments conducted for 12 distinct geographical regions, reflecting climate & pest pressure differences
    • One region split into two residential assessments
  • CRA assessments conducted for 7 distinct geographical regions (combined similar regions)
regional framework
Regional Framework

Source: USDA ERS

sap recommendations
SAP Recommendations
  • Use more descriptive distributions
    • Uniform vs. lognormal
  • Utilize activity pattern information from surveys such as National Human Activity Pattern Survey (NHAPS)
lawn applicator exposure data
Lawn: Applicator Exposure Data
  • Application Type:
    • Granular push-type rotary spreaders
    • Hose-end sprayer: removed remaining use of trichlorfon since liquid formulations are applied by LCO’s
  • Clothing Types:
    • PCRA uniform distribution: Range of clothing
    • CRA lognormal distribution Short-sleeved shirt and short pants
lawn applicator exposure data181
Lawn: Applicator Exposure Data
  • Granular Applicator: Dermal Exposure
    • Preliminary CRA
      • Uniform Distribution: 0.02–7.6 mg/lb ai
    • CRA
      • Lognormal Distribution:
        • Mean: 0.69
        • Std Deviation: 0.36
        • 99th Percentile: 1.93
lawn post application exposure data
Lawn: Post-Application Exposure Data
  • Residue Transfer to Skin (transfer coefficient)
    • Choreographed Activities of Adults Measured Using Biological Monitoring, Vacarro 1996
      • Granular and sprayable formulation
      • Crawling, football, frisbee
    • Non-Scripted Activities of Children Measured Using Fluorescent Tracers, Black 1993
      • Mostly solitary play with toys and books.
      • Also activity such as cartwheels
lawn and public health post application
Lawn and Public Health: Post-Application
  • Adult TC: 1,930-13,200 cm2/hr
    • PCRA Uniform distribution (n=16 Vacarro)
  • Child TC: 700-6,000 cm2/hr
    • PCRA Uniform distribution: Vacarro (n=16) and Black (n=16)
lawn and public health post application184
Lawn and Public Health: Post- Application
  • CRA: e.g., children
    • Used Black data for spray formulations
      • 3348-16,008 cm2/hr (AM 7265, standard deviation 4621)
      • 99th percentile: 23,769
    • Used Vacarro data for granular formulation
      • 714-4785 cm2/hr (AM 2225, standard deviation 2162)
      • 99th percentile: 10,632
golf courses post application exposure data
Golf Courses: Post-Application Exposure Data
  • Dermal Contact
    • PCRA: Uniform distribution: 200 to 760 cm2/hr
    • Includes walking and using a cart
    • CRA: Lognormal distribution (AM 483; Standard Deviation 185)
      • 99th percentile 1066 cm2/hr
garden applicator exposure data
Garden: Applicator Exposure Data
  • Preliminary CRA:
    • shaker can (n-20):
      • uniform, 0.0034-0.356 mg/lb ai
    • small tank sprayer (n-20):
      • uniform, 7.99-354.4 mg/lb ai
  • Similar issues regarding clothing as in lawn applications
garden applicator exposure data187
Garden: Applicator Exposure Data
  • CRA:
    • Shaker can:
      • lognormal, AM 0.18, standard deviation 0.29
      • 99th percentile 1.31
    • Small tank sprayer:
      • lognormal, AM 78, standard deviation 76
      • 99th percentile 372
indoor inhalation exposure data
Indoor: Inhalation Exposure Data
  • Preliminary CRA: Post-application inhalation exposure (adults and children)
    • Pest strips: 0.005-0.11 mg/m3
      • Collins et al., 1973
  • Duration of time spent indoors, and breathing rates
    • Up to 24 hours, at rest to moderate
    • Rest to moderate met value (1-2)
indoor inhalation exposure data189
Indoor: Inhalation Exposure Data
  • E = C x BMR x H x VQ x MET_TIME
  • BMR – Basal Metabolic Rate
      • Specific to CSFII individual
  • MET_TIME – met values x duration
    • PCRA: e.g., 24 hrs x met value (2) = 48
indoor inhalation exposure data190
Indoor: Inhalation Exposure Data
  • CRA: Consolidated Human Activity Database (CHAD) hhtp://www.epa.gov/chadnet1
    • Compilation of preexisting human activity surveys collected at the national, state and city level
      • Generated random MET values for each indoor activity responses
      • Multiplied MET value by duration and generated distributions
cra met time values
CRA: MET_Time Values

Cumulative

Percentile

4-6 yr olds

18+

90th

41

40

95th

47

49

99th

59

67

pets applicator
PETS: Applicator
  • Empirical Cumulative Distributions
    • Applicator data applying TCVP using aerosols, powders and pump sprays
    • Applying to 1 to 4 dogs*
    • Dogs weighing up to 148 pounds*

* based on 176 dogs

pets post application
PETS: Post-Application
  • Dermal exposure based on exposure while individuals were applying pesticides and grooming treated pets
  • Chemical/formulation specific fur residues
    • Average transfer efficiencies of 2.79%
pets post application194
PETS: Post-Application
  • Child Dermal Contact Values
    • Average 673 cm2/hr
    • Range 66 to 1660 cm2/hr
  • Duration of contact based on video tapes of children playing with pets (n=3) Freeman et al., 2001; triangular distribution
    • minimum 0.0333 hrs
    • maximum 1.025 hours
    • mode 0.11
characterization
+ over estimate; - under estimate; ~ neutralCharacterization

Input Parameter

bias

assumptions uncertainty

Lawn Applicator: granular

~

high confidence – issues re: clothing. No impact

Shaker can

~ to +

high confidence, clothing, shrubs only. May overestimate

Tank sprayer

~

High confidence, clothing. No impact

Dermal Contact Transfer - lawns

- to +

Activities appear to be representative, but distributions may be reflective of study design rather than actual activities

Children: Spray study is based on a non-toxic substance (not a pesticide), high transfer efficiency (6%), assumed 1% for generating dermal contact values.

Golf: dermal

~

No impact

Met_Time

~ to +

May have some very high end individuals, truncation at 99th percentile did not have a significant impact.

Frequency, contact w/ pets

- to +

Based on video-observations of children, small n.

Dermal contact post appl pets lawn

~ to +

Shampooing and grooming immediately after treatment. Considerable contact.

Pet fur residues

~

Direct hand measurements. Chemical and formulation specific.

population exposed: pets

~ to +

Small population of users increased based on use of collars since we did not include a collar assessment.

slide196
Integrating Pathway-specific Exposures in a Cumulative Risk Assessment:

Region “A” Example

David J. Miller

Health Effects Division

outline
Outline
  • Background on Region “A”
  • Risk Equation
  • Key Concepts in Aggregation/Cumulation Methodology using DEEM™ /Calendex™
    • Importance of calendar-based Assessment
  • Illustrative step-by-step example of Probabilistic Aggregate/Cumulative Assessment for Food and Residential Exposures
  • Review Output/Results for Region “A” (Exposure Profile Plots)
florida region region a
Florida Region (Region A)
  • Food (Bill Smith):
    • National estimates (applied to all regions)
    • No seasonal/geographic component
  • Drinking Water (Nelson Thurman):
    • Region-specific estimates
    • PRZM-EXAMS daily water concentrations
    • Typical application rates
    • Accounts for application timing/co-occurrence
  • Residential (Jeff Evans):
    • Region-specific estimates
    • Distributional inputs
    • Accounts for application timing
florida region region a pesticide scenario combinations
Florida Region, Region “A”: Pesticide/Scenario Combinations

Table II.A.1. Pesticides and Use Sites/Scenarios Considered in Florida Residential/Non-Occupational and Drinking Water Assessment

risk equation
Risk Equation
  • Risk = f(Exposure, Hazard)
    • Hazard part derived from toxicological studies
    • Exposure part derived from
      • FOOD: residues and consumption
        • Oral pathway
      • WATER: residues and consumption
        • Oral pathway
      • RESIDENTIAL: residues and contact
        • Oral pathway
        • Dermal pathway
        • Inhalation Pathway
key concepts in cumulative assessment
Key Concepts in Cumulative Assessment
  • Important to “integrate” or combine these estimated exposures in an internally consistent manner to develop region-specific risk picture
    • Integrated (or Combined) Exposure = “Total MOE”
    • “Appropriate Matching and Combining”

1

  • MOEtotal =

1

1

1

+

+

MOEdermal

MOEoral

MOEinhalation

key concepts in cumulative assessment appropriate matching and combining
Key Concepts in Cumulative Assessment: “Appropriate Matching and Combining”
  • Objective: to appropriately match and subsequently combine estimates of pesticide exposures through food with estimates of pesticide exposures through residential uses and estimates of exposures through drinking water
key concepts in cumulative assessment appropriate matching and combining204
Key Concepts in Cumulative Assessment:Appropriate Matching and Combining
  • Matching and combining must appropriately consider temporal and spatial factors associated with exposure
    • Temporal Factors
      • The time of year that pesticide exposures occur
        • E.g., springtime
      • Pesticide exposures on one day can be related to pesticide exposures on previous day
        • E.g. day-to-day relationships
    • Spatial Factors
      • Region of Country in which pesticide exposures occur
        • E.g., South vs. North
deem calendex cumulative assessment
DEEM™/Calendex™ Cumulative Assessment
  • DEEM™/Calendex™ provides a probabilistic assessment in which appropriate matching occurs
    • Incorporates concept of a Calendar to evaluate aggregate exposures
    • Looks at each individual day of the year
      • Allows appropriate “temporal matching” of exposures through food, drinking water, and residential pathways.
      • Temporal aspect of exposure through residential and agricultural uses important for OP pesticides due to expected seasonal use-patterns
deem calendex cumulative assessment206
DEEM™/Calendex™ Cumulative Assessment
  • What would happen if we didn’t use calendar-based approach?
  • For example:
    • Fall dermal exposure through lawn-use could be (incorrectly) combined with dermal exposure through spring flea treatment on pets
    • Oral hand-to-mouth exposure from spring lawn application on one day could be (incorrectly) combined with drinking water concentration characteristic of the winter season
key concepts in cumulative assessment appropriate matching and combining207
Key Concepts in Cumulative Assessment:Appropriate Matching and Combining
  • In summary, must track potentially exposed persons on a daily basis in a way that preserves all appropriate linkages in a way that considers time, region, and age groups
calendex concepts
Calendex™ Concepts
  • Calendex™ uses probabilistic techniques to appropriately combine exposures from the food, water, and residential pathways in a manner which incorporates:
    • Probabilities of exposure,
    • Use and application practices,
    • Human activity patterns,
    • Etc.

and considers their associated seasonality and timing

  • Result is a collection (or distribution) of aggregated/cumulated exposures (food, residential, and drinking water combined) for each day of the year for the relevant region

These exposures can be plotted as a “time-line” or profile of daily exposures for any given percentile in the distribution

illustrative example of calendex analysis
Illustrative Example of Calendex™ Analysis
  • 1-day exposure is presented as an example
  • Analysis serves as “building block” for any number of days analysis
  • Only oral pathway is considered
illustrative example of calendex analysis211
Illustrative Example of Calendex™ Analysis
  • Hypothetical Consumption Profile for CSFII Individual #1
    • 12 kg child
    • Consumed: 260 g food #1

320 g food #2

250 g food #3

  • Period of Interest: January 1 through December 31
  • Specific to Region of Interest
illustrative example of calendex analysis212
Illustrative Example of Calendex™ Analysis
  • STEP 1: Calculate Exposure from Food for Individual #1 on January 1
    • Food Exposure(from DEEM™): = 2.89x 10-5 mg/kg bw/day
  • STEP 2: Select Water Consumption for Individual #1
    • E.g., 1560 mL
  • STEP 3: Randomly select year from multiple years of daily water values
illustrative example of calendex analysis213
Illustrative Example of Calendex™ Analysis
  • STEP 4 : Assign the Water Concentration from January 1 from that year to Individual #1
  • STEP 5: Calculate Exposure from Water by pairing water consumption value with selected water concentration value for January 1

Water: (1560 mL x 0.00053 mg/L)/62 kg = 1.33 x 10-5 mg/kg bw/day

  • STEP 6: Aggregate with Food Exposure for January 1

1.33 x 10-5 + 2.89 x 10-5 = 4.22 x 10-5 mg/kg bw/day

illustrative example of calendex analysis214
Illustrative Example of Calendex™ Analysis
  • STEP 7: Select Residential Treatments for Individual #1 on January 1
    • Specific to region & time and demographics of individual
    • Assigned probabilistically
      • Were pesticides applied in/around home?
      • If so, which treatments?
        • And how much, how often, during what time frame, with what frequency, and by whom?
  • STEP 8: Calculate Exposure from any assigned new residential uses for January 1
illustrative example of calendex analysis215
Illustrative Example of Calendex™ Analysis
  • STEP 9: Determine if Exposure is “Active” from any previously assigned use/application
    • by oral (hand to mouth) exposure to children (2 days earlier)

= 1.33 x 10-5 mg/kg BW/day

  • STEP 10: Aggregate exposures for Day #1 from Food/Water, and (any active) Residential Uses

= 2.89x 10-5 mg/kg BW/day + 1.33 x 10-5 mg/kg BW/day

= 4.22x 10-5 mg/kg BW/day

illustrative example of calendex analysis216
Illustrative Example of Calendex™ Analysis
  • STEP 11 : Repeat Steps 1-10 many additional times for this individual, randomly selecting a series of treatment scenarios for that year, determining if any are applicable or otherwise “active” for Day #1 for that individual, and aggregating (summing) selected food/water and residential exposures
  • STEP 12: Continue steps 1-11 with Individual #2 through Individual # ~20,000
    • Result is a collection (or distribution) of aggregate exposures for January 1 for the relevant region
illustrative example of calendex analysis217
Illustrative Example of Calendex™ Analysis
  • STEP 13: Repeat steps 1-12 for January 2
    • Result is a collection (or distribution) of aggregate exposures for January 2 for the relevant region
  • STEP 14: Repeat steps 1-13 for January 3 through December 31
    • Result is a collection (or distribution) of aggregate exposures (food, water, and residential combined) for each day of the year for the relevant region
    • These exposures can be converted to MOEs and plotted as a “time-line” or profile of daily exposures for any given percentile in the distribution
example of calendex analysis time based exposure profile
Example of Calendex™ Analysis(time based exposure profile)

Children 1-2

1-day

99.9th Percentile

Day of the Year

example of calendex analysis time based exposure profile219
Example of Calendex™ Analysis(time based exposure profile)

Children 1-2

1-day

99th Percentile

Day of the Year

rolling time frame approach
Rolling Time-Frame Approach
  • In a rolling time frame approach, average exposures over multiple days are calculated for each individual
    • e.g., January 1 through 7, then January 2 through 8, January 3 through 9, etc.
    • This series of multi-day average exposures serves as basis of comparison with POD
example of calendex analysis time based exposure profile221
Example of Calendex™ Analysis(time based exposure profile)

Children 1-2

7-day

99.9th Percentile

Day of the Year

example of calendex analysis time based exposure profile222
Example of Calendex™ Analysis(time based exposure profile)

Children 1-2

7-day

99th Percentile

Day of the Year

summary223
Summary
  • Food, water, and residential exposures were considered probabilistically in the cumulative assessment
    • Reflects realistic pesticide use based on pest pressures, weather, activity patterns, etc.
    • Temporal and spatial characteristics were preserved and maintained to produce realistic assessments
summary224
Summary
  • Result of Assessment is a time based exposure profile of exposures at any selected percentile
    • Total Exposure
    • Various pathway specific exposures
slide225
Risk Characterization

Margaret J. Stasikowski

Director,

Health Effects Division

risk characterization226
Risk Characterization
  • Interpretation of the Assessment
  • Particularly important in a complex assessment
  • Synthesis of information about the input data
  • Synthesis of information about the processing of data
  • Interface between the risk assessment and risk management
risk characterization227
Risk Characterization
  • Strengths and weaknesses of data used
  • Bias and direction of bias in input parameters
  • Uncertainty surrounding the input data
  • Uncertainty in use of models
risk characterization228
Risk Characterization

No single value in the assessment should be used to independently arrive at the interpretation of the results

road map to risk characterization
Road Map to Risk Characterization
  • Use of Regional Assessments
  • Hazard and Dose-Response
  • Modes of Analyses and use of Calendex™
  • Food
  • Residential
  • Drinking Water
  • Conclusions
use of regional assessments
Use of Regional Assessments
  • Regional Assessments
    • Regional assessments integrate food, residential, and drinking water assessments into one output
      • Keep in mind, however, that food is nationally assessed
      • Residential and drinking water are regionally assessed
    • Residential and drinking water risk are not of concern
      • Except for residential pest strip use
  • Risk characterization, therefore, concentrates on hazard dose-response and exposures through food
hazard and dose response
Hazard and Dose-Response
  • Brain Acetylcholinesterase inhibition reflects response in a target tissue relevant to humans
    • Error due to extrapolation from a surrogate tissue eliminated
    • Data have narrow confidence limits
      • Much less variability
hazard and dose response232
Hazard and Dose-Response
  • Relative Potency Factor approach
    • Utilizes entire dose response curve rather than less accurate NOAEL method
    • Biological or pharmacokinetic modeling would be better
      • However, input parameters not available
    • Applied simple dose addition
hazard and dose response233
Hazard and Dose-Response
  • Exponential model used
    • Adjusted to appropriately reflect inhibition at very low doses
    • Modified to generate limiting values for each OP
    • Curve fit empirically
hazard dose response
Hazard Dose-Response
  • Dose additivity
    • Additivity assumes dose-response curves are parallel
      • Underlying biological processes for each OP complex
      • Activation and/or deactivation rates differ for some OPs
      • Insufficient data to separate into subgroups
    • Uncertainty exists in assuming additivity because horizontal asymptotes are heterogeneous among the OPs
hazard dose response235
Hazard Dose-Response
  • Dose additivity assumption uncertainties
    • Does additivity apply to all of the OPs at human exposure levels?
    • Does additivity slightly overestimate or underestimate response because of assumption that response is uniform regardless of the underlying background exposure level?
hazard dose response236
Hazard Dose-Response
  • BMD10 used as a point of comparison
    • Point in the observed response range
    • Low enough to reduce impact of any lack of proportionality
    • Reliably distinguishable from background
hazard dose response237
Hazard Dose-Response
  • Index Chemical – Methamidophos
    • Excellent data to support modeling BMD10 for the three routes of exposure
    • BMD10 and BMDL nearly the same
hazard dose response238
Hazard Dose-Response
  • Use of Steady State Cholinesterase Inhibition
    • Steady state reached about day 21
    • Point at which further ChE inhibition is offset by regeneration of the enzyme and equilibrium has been achieved
    • Stable, reproducible levels of inhibition in all compartments measured
    • EPA assumes no naïve exposures to OPs
      • Consistent with the results of biomonitoring studies
    • Regeneration of ChE in days to weeks expected
hazard dose response239
Hazard Dose-Response
  • Uncertainties surrounding use of steady state
    • May over- or underestimate risk
    • Extent and direction of the error not known
    • Data pertaining to prior exposure to humans different from that used in rat feeding studies
  • Even with these uncertainties, EPA believes that steady state provides a reasonable endpoint for hazard dose-response
    • SAP agreed that this endpoint is appropriate
use of calendex and the mode of analysis
Use of Calendex™ and the Mode of Analysis
  • Single day analysis
    • Exposures on consecutive days at the same percentile are unlikely to be the same individual
    • Consecutive single-day estimates of exposure are likely to significantly overestimate multi-day exposures to an individual (at higher percentiles)
  • Seven day rolling average
    • Exposures more directly comparable to multi-day toxicity endpoint
    • Better incorporates variability in exposure for an individual across multiple days
    • Will not capture a single day “spike” exposure
    • Consumption and residue data not designed for linked-series of days analysis

In both cases associated ChEI level is underestimated because lingering ChEI effect is not accounted for

use of calendex and the mode of analysis241
Use of Calendex™ and the Mode of Analysis
  • 14 and 21 day averaging also possible
    • Incrementally small decreases in the estimated risk
    • With longer averaging time one approaches the mean exposure for the output distribution
      • Obscures time-related variability in exposure
use of calendex and the mode of analysis242
Use of Calendex™ and the Mode of Analysis
  • Use of CSFII Data
    • Single day analysis
      • Consumption diary records for each individual paired with a randomly selected set of residue values
        • Uses each available day of consumption data
      • Arrayed as a distribution from high to low exposures
      • Assumes consumption of foods independent from day to day
      • Overemphasizes variability
use of calendex and the mode of analysis243
Use of Calendex™ and the Mode of Analysis
  • Use of CSFII Data
    • Seven day rolling average
      • One diary for each individual paired with a randomly selected set of residue values
        • Randomly redraws from two available days of consumption data over time period of interest (e.g., seven days)
      • Assumption that diet of every individual is limited to the records in the diaries repeated randomly
      • Variability in the diet may not be fully expressed
use of calendex and the mode of analysis244
Use of Calendex™ and the Mode of Analysis
  • Impact of residual cholinesterase inhibition
    • Inhibition not immediately reversible
    • Any day exposure includes inhibition from previous days (carry-over effect)
    • One day analysis does not incorporate this
    • Seven day captures carryover of exposure but not biological aspect of declining exposure over time
    • Seven day de-emphasizes impact of intermittent high exposure
food assessment characterization
Food Assessment Characterization
  • Consumption Data
    • 1994 – 96, 98 CSFII realistic estimate
    • Adequate number of samples
      • Increased accuracy and utility
    • Extremes of the distribution less well represented than those reflecting the central tendency
      • Some uncertainty at the tails
      • Consumption records in the tail of the distribution analyzed
        • No indication that any small subset of consumption records dominates the outcome of the assessment
food assessment characterization246
Food Assessment Characterization
  • PDP Monitoring Data
    • Directly measures occurrence of more than one OP in a sample
    • Composite analysis may slightly understate potential risk
    • Samples with non-detectable residues assumed zero values
      • Sensitivity analysis showed negligible impact
food assessment characterization247
Food Assessment Characterization
  • Data translation from PDP
    • Families of commodities with similar cultural practices and insect pests likely have similar pesticide use
    • Perhaps introduces uncertainty
    • Not many commodities translated
      • Translated commodities ~1% of child’s diet
food assessment characterization248
Food Assessment Characterization
  • Other Sources of Residue Data
    • FDA Total Diet Study & monitoring data
      • For meats, seafood and eggs, negligible residues assumed
    • 3% of the foods for 1 – 2 year olds unaccounted for
      • Highly processed and blended
      • Negligible residues assumed
    • Do not expect any impact on the assessment
food assessment characterization249
Food Assessment Characterization
  • Impact of Regulatory Actions
    • Existing agreements on removal of uses
      • Uses taken out of the assessment
    • Changes in use patterns not yet reflected in monitoring data
      • Increased pre-harvest intervals
      • Reduced rates of application
    • Ongoing regulatory process for some chemicals
    • All types of regulatory actions will likely result in further reduction of exposure
food assessment characterization250
Food Assessment Characterization
  • Model Outputs
    • Single-day food assessment using DEEM
    • Seven-day rolling average using Calendex™
    • 14 and 21-day analyses included for Region A
food assessment characterization251
Food Assessment Characterization
  • Based on experience with individual chemical assessments
    • Assumption that OP exposure in food uniform nationally
    • Assumption of no significant seasonal variations
      • Ability to store and preserve food, import of seasonal foods
      • PDP does not suggest different types and magnitude of pesticide use across the year
  • Food assessment uncertainties
    • Does not reflect highly localized consumption
    • Only small percentage of food affected
food assessment characterization252
Food Assessment Characterization
  • Toxicity endpoints developed in consideration of 10X factor for interspecies variability and 10X factor for intraspecies variability
  • The additional FQPA Safety Factor is included as an adjustment to the chemical-specific RPFs
  • For the single day analysis for food, MOEs calculated using DEEM software rather than Calendex™
food assessment characterization254
Food Assessment Characterization
  • MOEs from the 7-day analysis exceed 100 at all percentiles of output distribution
  • MOE for the single day assessment at the 99th percentile of output distribution is 128 for children 1-2 and 158 for children 3-5
  • MOE for the single day assessment at the 99.9th percentile of output distribution is 45 for children 1-2 and 53 for children 3-5
  • MOE reaches 100 at the 99.4th percentile of exposure for the single day analysis for children 1-2
food assessment characterization255
Food Assessment Characterization
  • OPP believes that 99.9th percentile of exposure in the single-day assessment is an upperbound of anticipated exposure
    • Especially when considering that exposure at such a high percentile is not expected to occur often
    • Does not reflect changes in residues from recent mitigation actions
  • MOE at the 99.9th percentile of output distribution for 1-day likely overstates the risk from OPs in food
food assessment characterization256
Food Assessment Characterization
  • EPA believes exposures in the U.S. fall somewhere between the results of the single day and seven day analysis
slide257
Most Significant Chemicals in the Top 0.2 Percentile

Of Exposure for Children 1-2

Chemical

Percentage of

Total

Exposure

Dimethoate/Omethoate

48 %

Azinphos methyl

27%

Acephate/methamidophos

11%

Methamidophos

5%

Phosmet

2.4%

Phorate

2.2%

slide258
Most Significant Foods In Top 0.2 percentile

of Exposure for Children 1-2

Food

Food Form

Fraction of Total Exposure

Grape

Uncooked; Fresh or N/S; Cook Meth N/S

0.33

Pear

Uncooked; Fresh or N/S; Cook Meth N/S

0.16

Apple, fruit with peel

Uncooked; Fresh or N/S; Cook Meth N/S

0.13

Apple, juice

Uncooked; Fresh or N/S; Cook Meth N/S

0.10

Tomato

Uncooked; Fresh or N/S; Cook Meth N/S

0.05

Grape, raisin

Uncooked; Dried; Cook Meth N/S

0.04

Bean, snap, succulent

Cooked; Frozen; Boiled

0.03

Pepper, bell

Uncooked; Fresh or N/S; Cook Meth N/S

0.03

Bean, snap, succulent

Cooked; Canned; Boiled

0.02

All Other Commodities

 0.01

food assessment characterization259
Food Assessment Characterization
  • Individual assessments for some of these chemicals still need to be completed
  • All information in risk characterization including sensitivity analyses need to be taken into account
residential assessment characterization
Residential Assessment Characterization
  • Conducted for seven regions
  • Distributional analysis
    • Log normal
  • Factored in seasonal aspects of pesticide use
residential assessment characterization261
Residential Assessment Characterization
  • Exposure Contact and Pesticide Residue Dissipation
    • Robust information, OPP has high confidence in the use of these data
  • Specific pesticide use data available and used in distributional analysis
  • Calendex™ inputs adjusted to reflect regional use patterns
  • Non-dietary ingestion assessed
    • Children mouthing behavior (hand-to-mouth)
    • Limited data available describing mouthing behavior
    • EPA believes frequency of hand-to-mouth estimates used in current assessment may overstate risk
residential assessment characterization262
Residential Assessment Characterization
  • Results
    • Use of DDVP in No-Pest strips major contributor to exposure
      • Only remaining indoor use of OPs
      • Removal of DDVP from assessment in sensitivity analysis resulted in MOEs approximately the same as for food alone
    • Hand-to-mouth activities by children in conjunction with lawn exposure in southern regions is important
      • Uncertainty regarding the estimate of exposure likely to overestimate
drinking water characterization
Drinking Water Characterization
  • Represents one of most vulnerable drinking water sources in each region
    • Surface water source (reservoir)
    • High OP use in vicinity of water body vulnerable to pesticide contamination
    • Protective of region
  • Daily distributions estimated using PRZM/EXAMS Index Reservoir
    • Comparisons with monitoring indicate estimates are reasonable
drinking water characterization264
Drinking Water Characterization
  • Represent typical OP uses based on actual use surveys
    • If all OP pesticides were used at maximum rate, distributions may increase by no more than a factor of 2-4X
    • Low likelihood that all OP pesticides would be used at maximum rates in same year
  • Distributions represent variations in expected concentrations due to year-to-year weather variations
drinking water characterization265
Drinking Water Characterization
  • Results
    • OPs in drinking water are not major source of cumulative exposure in most regions
    • In two regions (A, G), drinking water exposure approached food exposure levels on brief periods
      • In A, refined concentrations lower because of sugarcane water management
      • In A and G, regional exposure represent high-end sites that don’t reflect what majority of population drinks
drinking water characterization266
Drinking Water Characterization
  • Drinking water treatment effects
    • Not enough information for quantitative evaluation
    • Evidence suggests transformation to oxons, sulfones, sulfoxides
    • Assessment already accounts for sulfones, sulfoxides
    • “Worst-case” evaluation for oxons (100% conversion, 10X increase in toxicity) found no impact on cumulative exposure from water
risk characterization conclusions
Risk Characterization Conclusions
  • OPP advanced risk assessment methods as it developed OP cumulative assessment
    • State of the art
  • Extensive peer review of methods and assessment
  • Assumptions in many parts of the assessment were replaced with data
risk characterization conclusions268
Risk Characterization Conclusions
  • Refined picture of exposure likely to be encountered in the real world
  • Uses distributions of data wherever possible
    • Permits use of the full range of values for each parameter
  • Results as a range of MOEs using one-day and seven-day rolling averages at different percentiles of exposure distribution
risk characterization conclusions269
Risk Characterization Conclusions
  • EPA believes real world exposure lies somewhere between the one-day and seven-day rolling average
  • Continued analysis of exposures that are significant at the lower end of the MOE range
  • Important not to focus on a single number
risk characterization conclusions270
Risk Characterization Conclusions
  • Individual OP assessments and mitigation actions need to be finalized
  • Few uses of OPs on food crops play a larger role in the results of the food assessment
risk characterization conclusions271
Risk Characterization Conclusions
  • Residential risk assessment
    • OP exposure no longer plays a significant role in the cumulative risk from OPs
    • DDVP pest strip major contributor to the cumulative risk assessment
    • Single chemical risk mitigation underway
  • Drinking water assessment
    • OP exposure does not play a significant role in the cumulative risk
summary and conclusions

Summary and Conclusions

Lois Rossi, Director

outline of discussion
Outline of Discussion
  • Background Information
  • Status of Individual Chemical Risk Mitigation
  • Summary of Important Risk Concerns
  • Risk Characterization
    • Risk Management Point of View
  • Next Steps
introduction
Introduction
  • Continuing to follow course laid out for the Cumulative Assessment over the last five years
  • Sharing current state of our knowledge to the fullest extent possible
  • Inviting public comment and scientific peer review on remaining risk assessment and science policy issues
  • Prepared extensive risk characterizations
background information
Background Information
  • It appears that exposure from water is not a significant contributor to the OP cumulative risk estimates
  • The only residential use that plays an important role in the risk estimate is the indoor use of DDVP (pest strips)
    • Individual chemical risk management for DDVP has not been completed
    • Currently working with registrants on mitigation
    • EPA is committed to addressing this risk and is hoping to quickly resolve this concern
background information cont
Background Information (Cont.)
  • Individual chemical risk mitigation for dietary risks has been addressed for all OPs except:
    • Dimethoate/omethoate
    • Malathion
    • DDVP
    • ODM
    • Tetrachlorvinphos
  • Although IREDs have not yet been completed for diazinon and methyl parathion, dietary risks have been addressed in previous mitigation action
key risk estimate elements
Key Risk Estimate Elements
  • Relatively few chemical/crop combinations play a major role in the OP cumulative risk assessment
  • Not meant to imply that risks are such that exposure from any one chemical/crop combination must be addressed or that all of them must be addressed
risk management considerations
Risk Management Considerations
  • Integrate all of the information from the various components of the assessment
  • Look at:
    • Strengths and weaknesses of data
    • Potential biases in input parameters and the direction of that bias
    • Uncertainties in the data and exposure models, and try to bound that uncertainty
  • One way to examine uncertainties in data or models is to develop estimates based on other sources of data or other models
summary279
Summary
  • Appears that a major factor influencing the results is that a few individual OP risk assessments have not been finalized and resulting risk management actions have not been taken
  • This is particularly true for DDVP and Dimethoate
comments on revised assessment
Comments on Revised Assessment
  • Revised assessment has been released for public comment
  • Assessment relies on extensive set of rich databases and many newly developed methods and model(s)
  • Agency hopes that this discussion of considerations in charactizing the OP cumulative risk will help focus comments
  • It is important to focus on these elements and considerations that really affect the results and are critical to making a regulatory determination
next steps
Next Steps
  • CARAT workgroup meeting (June 19)
  • Transition workgroup meeting (June 20)
  • Consultation with SAP (June 25-26) on science issues related to application of FQPA safety factor in the OP cumulative assessment
  • 30 day public comment period
  • Complete remaining individual chemical risk mitigation